Software Cost Estimation COMP 3663 D. L. Silver, Ph.D.

Software Cost Estimation Predicting the resources required for a software development process

Topics covered Feasibility Analysis Productivity measures Estimation techniques Algorithmic cost modelling Project duration

Feasibility Analysis Feasibility – the measure of how beneficial or practical an information system will be to an organization. Feasibility analysis – the process by which feasibility is measured. No additional notes.

Three Tests For Feasibility Technical feasibility – a measure of the practicality of a technical solution and the availability of technical resources and expertise. Economic feasibility - a measure of the cost-effectiveness of a project or solution. Operational feasibility – a measure of how well a solution will work or be accepted in an organization. Teaching Notes Emphasize that all candidates should be analyzed according to all of the above criteria. Students should understand that rarely will any one candidate solution be the most feasible candidate according to all criteria.

Economic Feasibilty = Cost-Benefit Analysis Costs: Development costs are one time costs that will not recur after the project has been completed. Operating costs are costs that tend to recur throughout the lifetime of the system. Such costs can be classified as: Fixed costs — occur at regular intervals but at relatively fixed rates. Variable costs — occur in proportion to some usage factor. Benefits: Tangible benefits are those that can be easily quantified. Intangible benefits are those benefits believed to be difficult or impossible to quantify. Teaching Notes Our experience suggests that students will need examples of each. The chapter includes several examples. Try providing the students with a list of items and ask them to classify them as a cost or benefit and to distinguish between the type of cost or benefit. While students tend to understand intangible benefits, they may have some difficulty in quantifying them. An exercise or two will help to reinforce the fact that intangible benefits can indeed be quantified.

Three Popular Techniques to Assess Economic Feasibility Payback Analysis Return On Investment Net Present Value The Time Value of Money is a concept that should be applied to each technique. The time value of money recognizes that a dollar today is worth more than a dollar one year from now. Teaching Notes While the textbook covers only the above popular techniques, it is important to stress that there may be others that organizations choose to use in assessing the economic feasibility of an investment. Stress the importance of determining the investment decision-making process or techniques used by the organization. It should also be pointed out that sometimes the techniques vary according to the individuals involved.

Software cost components Hardware and software costs Travel and training costs Personnel costs (the dominant factor in most projects) salaries of people involved in the project benefits and insurance costs Must also take project overhead into account costs of building, heating, lighting costs of networking and communications costs of shared facilities (e.g library, staff restaurant, etc.)

Costs for a Proposed System No additional notes.

Fundamental estimation questions How much effort is required to complete an activity? How much calendar time is needed to complete an activity? What is the total cost of an activity? Project estimation and scheduling are interleaved management activities

Costing and pricing Estimates are made to discover the cost, to the developer, of producing a software system There is not a simple relationship between the development cost and the price charged to the customer Broader organisational, economic, political and business considerations influence the price charged

Productivity measures Size related measures based on some output from the software process. This may be lines of delivered source code, object code instructions, etc. Function-related measures based on an estimate of the functionality of the delivered software. Function-points are the best known of this type of measure

Measurement problems Estimating the size of the measure Estimating the total number of programmer months which have elapsed Estimating contractor productivity (e.g. documentation team) and incorporating this estimate in overall estimate

Lines of code What is a line of code? Productivity measures will vary from language to language – consider difference between lines of code in assembler versus Java Relationship to functionality must be based on past efforts in the same language

Productivity estimates - LOC System Category LOC/person-month Real-time embedded systems 40-160 Systems programs 150-400 Commercial applications 200-800

Productivity estimates – Function points Based on a combination of program characteristics external inputs and outputs user interactions external interfaces files used by the system A weight is associated with each of these The function point count is computed by multiplying each raw count by the weight and summing all values

Function points Function point count modified by complexity of the project FPs can be used to estimate LOC depending on the average number of LOC per FP for a given language LOC = AVC * number of function points AVC is a language-dependent factor varying from 200-300 for assemble language to 2-40 for a high-level languages FPs are very subjective. They depend on the estimator. Automatic function-point counting is impossible

Factors affecting productivity

Quality and productivity All metrics based on volume/unit time are flawed because they do not take quality into account Productivity may generally be increased at the cost of quality It is not clear how productivity/quality metrics are related If change is constant then an approach based on counting lines of code is not as meaningful

Estimation techniques There is no simple way to make an accurate estimate of the effort required to develop a software system Initial estimates are based on inadequate information in a user requirements definition The software may run on unfamiliar computers or use new technology The skills of people working on the project may be unknown Project cost estimates may be self-fulfilling The estimate defines the budget and the product is adjusted to meet the budget

Estimation techniques Expert judgement Estimation by analogy Parkinson's Law Pricing to win Algorithmic cost modelling

Expert judgement One or more experts in both software development and the application domain use their experience to predict software costs. Process iterates until some consensus is reached. Advantages: Relatively cheap estimation method. Can be accurate if experts have direct experience of similar systems Disadvantages: Very inaccurate if there are no experts!

Estimation by analogy The cost of a project is computed by comparing the project to a similar project in the same application domain Advantages: Accurate if project data available Disadvantages: Impossible if no comparable project has been tackled. Needs systematically maintained cost database

Parkinson's Law The project costs whatever resources are available (typically used within an organization) Advantages: No overspend Disadvantages: System is usually left unfinished

Pricing to win The project costs whatever the customer has to spend on it Advantages: You get the contract Disadvantages: Costs do not accurately reflect the work required. Either: The customer does not get the desired system, or The customer overpays.

Pricing to win This approach may seem unethical and unbusiness-like However, when detailed information is lacking it may be the only appropriate strategy The most ethical approach: The project cost is agreed on the basis of an outline proposal and the development is constrained by that cost A detailed specification may be negotiated or an evolutionary approach used for system development

Top-down and bottom-up estimation Any of these approaches may be used top-down or bottom-up Top-down Start at the system level and assess the overall system functionality and how this is delivered through sub-systems Bottom-up Start at the component level and estimate the effort required for each component. Add these efforts to reach a final estimate

Top-down estimation Can be used without knowledge of the system architecture and the components that might be part of the system Takes into account costs such as integration, configuration management and documentation Can underestimate the cost of solving difficult low-level technical problems

Bottom-up estimation Usable when the architecture of the system is known and components identified Accurate method if the system has been designed in detail May underestimate costs of system level activities such as integration and documentation

Estimation methods Each method has strengths and weaknesses Estimation should be based on several methods If these do not return approximately the same result and the differences cannot be reconciled, there is insufficient information available Some action should be taken to find out more in order to make more accurate estimates

Experience-based estimates Estimating is primarily experience-based However, new methods and technologies may make estimating based on experience inaccurate Object-oriented rather than function-oriented development Client-server systems rather than mainframe systems Many off-the-shelf components Component-based software engineering Use of new CASE tools and program generators

Algorithmic cost modelling A formulaic approach based on historical cost information and which is generally based on the size of the software Cost is estimated as a mathematical function of product, project and process attributes whose values are estimated by project managers

Algorithmic cost modelling Effort in PM = A ´ SizeB ´ M A is depends in on the type of software that is being developed (simple, moderate, embedded) [will vary 2.4- 3.5] Size is an estimate of the code size or other functional assessmemt [thousands of lines of code, ie. 5,400 LOC 5.4] B reflects the disproportionate effort for large projects over small projects [typically 1.0-1.5] M is a multiplier reflecting a combination of product, process and people attributes (e.g. desired reliability, reuse required, personnel capability and expereince, support facilities) [will vary up from 1.0] PM = person months

Estimation accuracy The size of a software system can only be known accurately when it is finished Several factors influence the final size Use of “off the shelf” components Programming language Distribution of system As the development process progresses then the size estimate becomes more accurate

Estimate uncertainty Estimate uncertainty: As the project progresses the probablilty of a difference in actual to estimate decreases Actual person- months x = estimated person-months

COCOMO Constructive Cost Model An empirical model based on project experience Well-documented, ‘independent’ model which is not tied to a specific software vendor Long history from initial version published in 1981 (COCOMO-81) through various instantiations to COCOMO 2 COCOMO 2 takes into account different approaches to software development, reuse, etc. Can be used as a sanity check

COCOMO 81 Effort (PM) = A * SizeB * M PM = person-months KDSI = thousand of delivered software instructions

Basic COCOMO Formulae (Boehm) Effort in Person-months = aKLOC b Duration in Months = c Effort d Where c = labour estimate, d = complexity of project type These values are selected from a table such as the one below. Software Project a b c d Organic 2.4 1.05 2.5 0.38 Semidetached 3.0 1.12 2.5 0.35 Embedded 3.6 1.20 2.5 0.32 (See page 105 of text) Due to Boehm [Bo]

Computing COCOMO Case Study Models Adapted from Software Engineering: An Object-Oriented Perspective by Eric J. Braude (Wiley 2001), with permission.

Workshop Estimate Actual 80 60 , 1 error 52.5 44 , 1 error?? 70 50 , 100% correct 37.5 45 , 1 error